In conventional control systems for automatic production volume estimation of items (bottles or cans for example) produced on a production line, the items carried along a transport path (on a conveyor, for example) are detected and counted, and encoded identification data included on each item is read out and decoded so as to identify each counted item. Sometimes, the encoded identification data is a barcode (a UPC, “Universal Product Code”, for example), including data corresponding to a product type and item identification information (for example, a bottle of beer of 33 cl of a certain brand). More generally, the encoded identification data include data corresponding to product type identification information. Other examples of such product type identification data are identifiers like SKU (“Stock Keeping Unit”), EAN (“European Article Number”), GTIN (“Global Trade Item Number”), APN (“Australian Product Number”) etc., which are well known to the skilled persons in the field of item identification. Based on the count value and on the read out product type and item identification information, the control system determines a production volume per product type and per item.
Such spreading of production volume according to product type and item type is necessary for correctly controlling a production volume, in particular for the purpose of taxation of goods.
However, as a consequence of errors, defects or frauds, encoded identification data on such items is not always reliable. For example, a barcode label corresponding to a bottle of 33 cl may be erroneously or fraudulently affixed onto a bottle of one liter. Errors may also be due to the own motion of the items on the line. For example, contrary to bottling lines, whereon the rotation of the bottles is generally precisely controlled (to make the label applicator correctly affix the labels onto the bottles), on canning lines it is more difficult to precisely control the rotation of the cans, because the cans are in contact with each other, and thus barcode reading errors can more frequently occur. Moreover, said problem worsens as the number of different types of items to be handled by a same production line increases.
This non-reliability may be one of the causes of considerable errors in production volume control, and the amount of taxes due for a production volume may well be underestimated. Moreover, even if the product type and item identification information are the correct ones, other information like tracing data may lack or may be wrong. This latter information is not only important for tax perceiption, but also for tracking purposes, against counterfeit goods. The lack of reliability of conventional item information makes that conventional control systems for automatic production volume estimation are not capable to always correctly assess the production volume per product type and per item. Also, the lacking reliability of tracing data makes difficult any further control of the produced items (for example, after the item has left the production line).